At its core, the financial sector is fundamentally built out of numbers, math and data, which makes it particularly ripe for transformation via Artificial Intelligence (AI). Banks have now begun to tap into the potential of cognitive AI technologies to automate and scale customer-facing financial management processes. This is where an advanced cognitive agent like Amelia can prove particularly valuable. Here are three ways cognitive AI can intelligently connect customers to their financial institutions.

No More “Banking Hours”

From the customer’s perspective, one of the most useful parts about a User Experience (UX) powered by AI is its ubiquity. Amelia is available to interact with users 24/7 through a variety of channels and she scales to meet demand. This means that users are never forced to wait in queue, nor do they ever need to wait for “normal banking hours” to manage their finances. This increased accessibility also directly benefits banks through expanded opportunities to generate revenue.

Modern consumers, particularly younger digital natives, expect services to be available at all times. This accessibility is particularly important when it comes to vital services related to personal finances. At the very least, the financial institutions that don’t make their services available to customers at all hours will find themselves at a competitive disadvantage.

Far Beyond Routine

Through the decades, many basic financial management tasks have been automated by technology (e.g. ATMs, IVR systems, or basic Web interfaces). These automations have empowered customers to independently execute many basic processes, which has subsequently allowed institutions to mitigate customer service overhead and reinvest those savings elsewhere in the business.

Digital colleagues like Amelia take financial self-service a step further, since she can execute cognitive tasks related to decision making in addition to transactional ones. This advanced functionality enables banks to automate complex, potentially-lengthy processes, such as onboarding for wealth management services or applying for a mortgage.

Amelia delivers these new dimensions of automation through an advanced Natural Language Interface (NLI), which allows her to understand and process a number of human utterances – even ones she hasn’t been specifically programmed to understand. Perhaps even more important, she has the ability to handle context switching, so users can go back and revisit previous answers in a process. For example, a customer at a bike shop is ordering a custom-made bike and says at the end of the order, “Actually, can we make the handlebars red instead of grey?” A bike shop employee would have no problem making this one change without starting over. This ability to jump around to different steps within a process can actually be difficult for many AI interfaces, but can be easily handled by Amelia. Context switching is particularly important for mitigating user frustrations during complex prolonged processes (e.g. mortgage origination).

Learning the Connections

When AI automates functions, it necessarily leaves a great deal of data in its wake (e.g. the types of transactions being performed by what types of customers at different times). By tapping into the pattern recognition capabilities of AI, banks can access highly detailed real-time insights.

For example, AI might notice a spike in customers of a certain age and income applying for second mortgages. The system could then notify the bank’s marketing team about this information to suggest they begin a campaign targeting this demographic with information on second mortgage options.

Modern consumers, particularly younger digital natives, expect services to be available at all times. This accessibility is particularly important when it comes to vital services related to personal finances.

This internal real-time data mining can also help make customer accounts more secure. For example, the system might notice several accounts transferring funds to a single, potentially fraudulent offshore account, which might indicate a phishing campaign or other breach. The system could then automatically notify the bank’s security team to investigate the issue before more damage takes place.

The financial sector has long been on the frontlines of technological evolution. As we enter the cognitive era, banks are once again leading the way. And just as computers, the Internet, and mobile devices completely reinvented the ways consumers connect with their finances, cognitive technologies promise to be just as transformative.

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